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Published on: December 10, 2016
Changes of poultry faecal microbiota associated with Clostridium difficile colonisation
Jure Skraban1, Saso Dzeroski, Bernard Zenko
1Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins, 1000 Ljubljana, Slovenia.
Veterinary Microbiology
|May 14, 2013
Summary
Poultry gut microbiota analysis revealed specific bacterial and fungal groups associated with Clostridium difficile colonization. Acidaminococcus intestini was more prevalent in C. difficile negative samples, highlighting distinct microbial markers in chickens.
Area of Science:
- Microbiology
- Animal Science
- Veterinary Medicine
Background:
- Clostridium difficile (C. difficile) is an opportunistic pathogen affecting poultry health.
- Understanding the complex gut microbiota is crucial for managing C. difficile infections in chickens.
- Previous studies have focused on human C. difficile microbiota, necessitating poultry-specific research.
Purpose of the Study:
- To analyze the bacterial, fungal, and archaeal microbiota in chicken fecal samples.
- To identify microbial signatures associated with C. difficile colonization in poultry.
- To explore the potential of machine learning for predicting C. difficile presence.
Main Methods:
- Analysis of 143 chicken fecal samples using denaturing high-performance liquid chromatography (DHPLC).
- Differentiation of bacterial, fungal, and archaeal groups within the microbiota.
- Application of machine learning (WEKA J48) to identify predictive microbial combinations.
Main Results:
- Distinct clusters of microbiota were identified, correlating with C. difficile presence/absence.
- Acidaminococcus intestini was significantly associated with C. difficile negative samples.
- Microbial diversity was influenced by animal age but not by C. difficile status.
Conclusions:
- Poultry gut microbiota composition differs between C. difficile positive and negative individuals.
- Specific bacterial and fungal groups, including A. intestini, are key indicators of C. difficile colonization status in chickens.
- Machine learning effectively identified microbial markers predictive of C. difficile colonization in poultry.
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